Glossary
Deep Learning
Definition
Deep learning is a type of machine learning that uses layered neural networks to learn complex patterns directly from raw data — the technique behind image recognition, speech, and modern language models.
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Key points
- Excels at messy, unstructured inputs — images, audio, and text — where simpler methods struggle.
- Learns features on its own from raw data, instead of a person hand-picking what to look for.
- Powers computer vision, voice recognition, and the large language models behind today's AI assistants.
- It's more powerful but needs more data and computing than simpler machine learning — not always the right tool for a small, structured problem.
Quick answer
Deep Learning — common question
No. Deep learning shines on complex, unstructured data like images and language, but it needs more data and compute. For many structured business problems — like forecasting from tabular data — simpler machine learning is faster, cheaper, and just as accurate.
Only if the problem calls for it. If you're working with images, audio, or free text, deep learning is often the right fit. If your data is neatly structured in tables, a lighter model usually does the job with less cost and complexity.
From concept to working product.
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